Hexiang Wang

544 total citations
21 papers, 345 citations indexed

About

Hexiang Wang is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Hexiang Wang has authored 21 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Pulmonary and Respiratory Medicine, 10 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Oncology. Recurrent topics in Hexiang Wang's work include Radiomics and Machine Learning in Medical Imaging (10 papers), Sarcoma Diagnosis and Treatment (9 papers) and Bone Tumor Diagnosis and Treatments (6 papers). Hexiang Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (10 papers), Sarcoma Diagnosis and Treatment (9 papers) and Bone Tumor Diagnosis and Treatments (6 papers). Hexiang Wang collaborates with scholars based in China. Hexiang Wang's co-authors include Dapeng Hao, Jihua Liu, Shaofeng Duan, Feng Hou, Pei Nie, Wenjian Xu, Cheng Dong, Jie Li, Yujian Wang and Shunli Liu and has published in prestigious journals such as American Journal of Roentgenology, BioMed Research International and Journal of Magnetic Resonance Imaging.

In The Last Decade

Hexiang Wang

18 papers receiving 344 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hexiang Wang China 12 211 188 80 68 61 21 345
Irene Piscioli Italy 11 69 0.3× 139 0.7× 51 0.6× 162 2.4× 63 1.0× 29 313
Kasia Owczarczyk United Kingdom 6 176 0.8× 99 0.5× 38 0.5× 53 0.8× 54 0.9× 13 269
Weidong Zhang China 14 94 0.4× 136 0.7× 54 0.7× 84 1.2× 111 1.8× 25 361
Ujwal Bhure Switzerland 11 132 0.6× 146 0.8× 44 0.6× 153 2.3× 251 4.1× 29 466
Massimo Petracchini Italy 10 201 1.0× 318 1.7× 63 0.8× 87 1.3× 37 0.6× 16 464
Lorraine G. Shapeero United States 12 61 0.3× 238 1.3× 171 2.1× 122 1.8× 55 0.9× 18 381
Camila Lopes Vendrami United States 13 152 0.7× 221 1.2× 26 0.3× 212 3.1× 155 2.5× 28 474
Raymond Endozo United Kingdom 13 281 1.3× 155 0.8× 22 0.3× 79 1.2× 101 1.7× 32 455

Countries citing papers authored by Hexiang Wang

Since Specialization
Citations

This map shows the geographic impact of Hexiang Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hexiang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hexiang Wang more than expected).

Fields of papers citing papers by Hexiang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hexiang Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hexiang Wang. The network helps show where Hexiang Wang may publish in the future.

Co-authorship network of co-authors of Hexiang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Hexiang Wang. A scholar is included among the top collaborators of Hexiang Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hexiang Wang. Hexiang Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Han, Xiaomeng, Guo Li, Qian Jiao, et al.. (2025). A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center study. Cancer Imaging. 25(1). 27–27.
2.
He, Bingxi, C. Y. Hu, Zaiyi Liu, et al.. (2024). ContraSurv: Enhancing Prognostic Assessment of Medical Images via Data-Efficient Weakly Supervised Contrastive Learning. IEEE Journal of Biomedical and Health Informatics. 29(2). 1232–1242. 4 indexed citations
3.
Wu, Zengjie, et al.. (2023). Lumbar MR-based radiomics nomogram for detecting minimal residual disease in patients with multiple myeloma. European Radiology. 33(8). 5594–5605. 4 indexed citations
4.
Li, Jie, Tongyu Wang, Fengyuan Man, et al.. (2022). Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study. European Radiology. 32(10). 6933–6942. 14 indexed citations
5.
Liu, Bo, He Wang, Hexiang Wang, et al.. (2022). The predictive potential of contrast-enhanced computed tomography based radiomics in the preoperative staging of cT4 gastric cancer. Quantitative Imaging in Medicine and Surgery. 12(11). 5222–5238. 4 indexed citations
6.
Liu, Shunli, Jia Guo, Song Liu, et al.. (2021). A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours. Cancer Imaging. 21(1). 20–20. 34 indexed citations
7.
Song, Yancheng, Jie Li, Hexiang Wang, et al.. (2021). Radiomics Nomogram Based on Contrast-enhanced CT to Predict the Malignant Potential of Gastrointestinal Stromal Tumor: A Two-center Study. Academic Radiology. 29(6). 806–816. 20 indexed citations
8.
Wang, Hexiang, Cong Sun, Qing Zhou, et al.. (2021). Preoperative CT-Based Deep Learning Model for Predicting Risk Stratification in Patients With Gastrointestinal Stromal Tumors. Frontiers in Oncology. 11. 750875–750875. 11 indexed citations
9.
Song, Yancheng, Jan Zhang, Hexiang Wang, et al.. (2021). A novel immune-related genes signature after bariatric surgery is histologically associated with non-alcoholic fatty liver disease. Adipocyte. 10(1). 424–434. 15 indexed citations
10.
Wang, Yong, et al.. (2021). Imaging features of lipoma arborescens. Acta Radiologica. 63(8). 1043–1050.
11.
Xu, Wenjian, Dapeng Hao, Xuejun Liu, et al.. (2020). A CT-based radiomics nomogram for differentiation of lympho-associated benign and malignant lesions of the parotid gland. European Radiology. 31(5). 2886–2895. 29 indexed citations
12.
Liu, Hao, et al.. (2020). Prediction of cancer-specific survival and overall survival in middle-aged and older patients with rectal adenocarcinoma using a nomogram model. Translational Oncology. 14(1). 100938–100938. 11 indexed citations
13.
Hao, Dapeng, et al.. (2020). Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade. American Journal of Roentgenology. 215(4). 963–969. 38 indexed citations
14.
Wang, Hexiang, et al.. (2019). Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas. Journal of Magnetic Resonance Imaging. 51(3). 791–797. 58 indexed citations
15.
Nie, Pei, Jie Wu, Hexiang Wang, et al.. (2019). Primary hepatic perivascular epithelioid cell tumors: imaging findings with histopathological correlation. Cancer Imaging. 19(1). 32–32. 22 indexed citations
16.
Wang, Hexiang, et al.. (2018). Chondromyxoid fibroma of the temporal bone: A case report and review of the literature. World Journal of Clinical Cases. 6(16). 1210–1216. 2 indexed citations
17.
Li, Jie, et al.. (2018). Castleman disease versus lymphoma in neck lymph nodes: a comparative study using contrast-enhanced CT. Cancer Imaging. 18(1). 28–28. 10 indexed citations
18.
Wang, Hexiang, et al.. (2018). CT and MRI Findings of Soft Tissue Adult Fibrosarcoma in Extremities. BioMed Research International. 2018. 1–7. 22 indexed citations
19.
Zhang, Chuanyu, et al.. (2018). Computed Tomography and Magnetic Resonance Imaging Manifestations of Spinal Monostotic Fibrous Dysplasia. Journal of Clinical Imaging Science. 8. 23–23. 1 indexed citations
20.
Li, Jie, et al.. (2018). Comparison of Computed Tomography and Ultrasonography in the Assessment of Hepatoblastoma. Journal of Medical Imaging and Health Informatics. 8(4). 676–681.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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